Triple

T23455510
Position Surface form Disambiguated ID Type / Status
Subject He Knew He Was Right E567911 entity
Predicate setting P1957 FINISHED
Object Exeter NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Exeter | Statement: [He Knew He Was Right, setting, Exeter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Exeter
Context triple: [He Knew He Was Right, setting, Exeter]
  • A. Exeter
    Exeter is a historic town in Rockingham County, New Hampshire, known for its colonial heritage and as the home of the prestigious Phillips Exeter Academy.
  • B. Exeter chosen
    Exeter is a historic cathedral city in Devon, England, known for its medieval architecture and role as a regional administrative and cultural center.
  • C. Exeter
    Exeter is a small borough in Luzerne County, Pennsylvania, situated in the Wyoming Valley near the Susquehanna River.
  • D. Exeter
    Exeter is a small town located in Otsego County in central New York State, known for its rural character and agricultural landscape.
  • E. Exeter
    Exeter is a small village in the Southern Highlands of New South Wales, Australia, known for its rural charm, cool climate, and English-style gardens and architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e2458b4c888190b1d7998f9862a558 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a696e6c48190a7159292cfe3362f completed April 29, 2026, 6:35 a.m.
Created at: April 17, 2026, 5:53 p.m.